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#!/bin/bash
#SBATCH -J diffusion # Job name
#SBATCH -p rtx #-dev
#SBATCH -N8 # Number of nodes and cores per node required
#SBATCH --ntasks-per-node=1
#SBATCH -t 47:59:59 # Duration of the job (Ex: 15 mins)
#SBATCH -oReport-%j # Combined output and error messages file
#SBATCH --mail-type=BEGIN,END,FAIL # Mail preferences
#SBATCH --mail-user=xiabin@gatech.edu
pwd
date
#module load anaconda3/2022.05 # Load module dependencies
#module load pytorch
#conda activate diffusers
conda env list
module list
python -c "import torch; print(torch.cuda.is_available(), torch.__version__, torch.__path__, torch.version.cuda)"
cat $0
MASTER_ADDR=$(scontrol show hostnames $SLURM_JOB_NODELIST | head -n 1)
MASTER_PORT=$((10000 + RANDOM % 10000)) #12355
export MASTER_ADDR=$MASTER_ADDR
export MASTER_PORT=$MASTER_PORT
srun python diffusion.py \
--num_new_img_per_gpu 50 \
--max_num_img_per_gpu 2 \
--gradient_accumulation_steps 5 \
--train "$SCRATCH/LEN128-DIM64-CUB16-Tvir[4, 6]-zeta[10, 250]-0809-123640.h5" \
#--resume outputs/model-N3000-device_count4-node2-epoch49-23040531 \
######################################################################################
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